Bio

Kaitlyn Lee is a MA/PhD student in Biostatistics at the UC Berkeley mentored by Alejandro Schuler. Her research interests are broadly in causal inference, machine learning, and methods research. She is interested in developing methods to answer real-world questions about health and social policy in a statistically rigorous manner. Her current work focuses on causal inference with continuous treatment variables.

Education

UC Berkeley | Berkeley, CA

PhD in Biostatistics | August 2022 - May 2027 (expected)

MA in Biostatistics | August 2022 - August 2024 (expected)

Harvard College | Cambridge, MA

AB in Physics with Statistics Secondary | August 2016 - May 2020

Awards and Fellowships

NSF GRFP Fellow | 2024 - 2027

Biostatistics DEIB Fellow | 2024

Stern Health Fellow | 2022 - 2027

UC Berkeley Berkeley Fellowship | 2022 - 2024

UC Berkeley Chancellor’s Fellowship | 2022 - 2023

Experience

Center for Targeted Machine Learning, UC Berkeley | Graduate Student Researcher | Fall 2023 - Present

Cornerstone Research | Senior Analyst | January 2017 - June 2022

Huybers Lab, Harvard University | Research Assistant | May 2020 - December 2020